Motion detection system and method

ABSTRACT

A method is presented for imaging an object. The method comprises imaging a coherent speckle pattern propagating from an object, using an imaging system being focused on a plane displaced from the object.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a National Stage of International Patent ApplicationNo. PCT/IL2008/001008, filed Jul. 21, 2008, which claims the benefit ofIsraeli Patent Application No. 184868, filed Jul. 26, 2007.

FIELD OF THE INVENTION

This invention is in the field of motion detection and recognition. Itis particularly useful for detection and recognition of motionsassociated with various sounds, for example heart beats and speech.

BACKGROUND

Motion identification is useful in a very broad range of applications,including for example manufacturing production control, surveillance,and biomedical applications. Various methods have been developed bywhich motion can automatically be identified including mechanical,electronical, optical and acoustical motion detection.

For example, optical motion detection can be performed by aspeckle-based technique, such as electronic speckle-patterninterferometry (ESPI). The ESPI has been used for displacementmeasurements and vibration analysis, aimed at amplitudes, slopes andmodes of vibration. Speckle-based techniques have also been used fordeformation measurement. The optical detection can be the only viableoption if the environment of a moving object hinders sound propagationor unpredictably alters it.

The acoustical detection is especially useful in environments preventinglight propagation from a moving object to an observer. For acousticaldetection, the motion to be detected needs to be associated with asound. However, the moving object's environment may not allowpropagation of sound beyond a certain distance range. In particular,this occurs when sounds are produced behind a window (e.g. inside of aroom). Likewise, motion of interest may be associated with sounds whichmay be remote or weak. If for any reason sounds decay before they reacha remote observer, sound detection should be indirect. This indirectdetection may be based on optical means.

In particular, considering the example of sounds produced behind awindow, they may be detected by detection of a laser beam reflectionfrom the window. For generation of the reflection, the laser beam may beprojected on the window. The reflection detection may be performed by anoptical interferometer. The sounds then can be extracted (recognized) byprocessing the interferometer's output electronic signal. Theinterferometer's output is indicative of sounds produced behind thewindow because sounds vibrate the latter and phase-modulate thereflection of the laser beam. However, in this interference-based sounddetection technique all sounds vibrating the window participate in thephase-modulation. Consequently, they are detected in sum (i.e. assuperposition) and for their separation a blind source separationprocedure needs to be performed. Also, in this technique, the projectionlaser and the detection interferometer module need to be placed in sucha way that the specularly reflected beam is directed towards thedetection module. This interference-based technique requires complicatedcalibration before the operation and error control during the operation.

Motion detection is useful in biomedical applications. For example, itcan be used for detection and controlling Coronary Heart Disease (CHD).The CHD, along with Congestive Heart Failure, is connected with theregional and global motion of the left ventricle (LV) of the heart: CHDtypically results in wall-motion abnormalities. For example, if localsegments of the LV wall move weakly, this condition is known ashypokinesia; if they do not move at all, this condition is akinesia; andif they move out of sync with the rest of the heart, this condition isdyskinesia. Sometimes motion in multiple regions, or the entire heart,is compromised. The beats of LV can be imaged in a number of ways. Themost common method of this is the echocardiogram—a test that uses soundwaves to create a moving picture of the heart. In this test,high-frequency sound waves are emitted by a transducer placed onpatient's ribs near the breast bone and directed toward the heart. Theechoes of the sound waves are picked up and transformed as electricalimpulses to an echocardiography machine. The machine converts theseimpulses into moving pictures of the heart.

Heart beats can be monitored by other methods, especially if lessdetailed picture is needed. For example, for the detection of heart rateand pulse there are three main techniques in use: (1) detecting bloodflow in the capillaries of a finger or ear lobe with an infrared sensor;(2) detecting the heart ECG electrical signal in the hand area; and (3)detecting the heart ECG electrical signal with chest electrodes,commonly attached to an elastic strap going around the chest. A timingcircuit measures the interval between each beat, averages the intervalsfor a short period of time and converts this into a heart rate readingexpressed in beats per minute. Typically, a user of a heart rate monitormust stop exercising and hold his or her finger on the sensor and bevery still, while measuring.

DESCRIPTION

There is a need in the art of a novel optical motion detectiontechnique, capable of indirect detection of sound and speech. Apresented here novel technique, developed by the inventors, and based onoptical imaging, has adaptations (versions, embodiments) useful for suchdetection. The technique is useful for detections of motions containinga tilt component.

The technique includes imaging of a coherent speckle pattern formed byan object or subject or, generally, a surface of interest. The patterncan be formed by illumination of the still or moving surface of interestby coherent light of a laser or another light source. Preferably, thesurface movement includes a tilt component. The surface movement can befor example of vibration type. The vibration can be caused by a sound orvibration itself can produce a sound, thus making the motion of thesurface of interest associated with the sound. The motion of the surfaceof interest is further termed herein motion of interest.

In the inventors' technique, the imaging employs focusing on a plane orsurface being between the moving surface and an imaging unit (lightdetecting surface) or on a plane or surface being behind the movingsurface. Such planes or surfaces are termed herein displaced planes.Planes being between the moving surface and the imaging unit are termedherein forward displaced planes; and planes being beyond the movingsurface, looking from the imaging unit, are called herein downwarddisplaced planes. In some embodiments, the imaging utilizes focusing ona forward displaced plane being in the far field from the movingsurface. Such planes or surfaces are termed herein far field forwarddisplaced planes. In some other embodiments, the imaging utilizesfocusing on a downward displaced plane being in the far field from themoving surface. Such planes or surfaces are termed herein far fielddownward displaced planes. While some of the considerations belowdirectly address the case of imaging that employs focusing on forwarddisplaced planes or far field forward displaced planes, theseconsiderations can be appropriately applied to the case of usingfocusing in downward displaced or far field downward displaced planes.

The inventors have found that at forward displaced planes a coherentspeckle pattern associated with the surface of interest becomesgenerally stationary, and at far field forward displaced planes thecoherent speckle pattern becomes even more stationary (substantiallystationary). The stationarity is in fact quasi-stationarity (approximatestationarity); it appears at forward displaced planes if the surface ofinterest, while moving, keeps its shape constant or changes this shaperelatively slowly. The (quasi) stationarity of the speckle patterneffectively restricts the speckle pattern variation to shifting incorrespondence with the motion of interest. This effect is most evidentat the far field forward displaced planes. This effect is not used intypical imaging techniques, utilizing focusing on the surface ofinterest.

It should be noted that the technique of the invention can be used forextraction of motion even in cases when only a certain region of thesurface of interest keeps its shape constant or changes its shapequasi-stationary: if a motion or sound to be detected is associated withthe whole surface of interest, then this motion or sound can beextracted from the motion of this region.

The stationarity also appears for downward displaced planes and farfield downward displaced planes. The speckle pattern may not reach theseplanes because the object separates them from speckle pattern's origin;for example the speckle pattern will not reach these planes if theobject (surface of interest) is opaque. This, however, does not precludeimaging with focusing on one of these downward displaced and far fielddownward displaced planes. The imaging unit focused at a downwarddisplaced plane will still receive the speckle pattern originated fromthe object, not from the downward displaced plane. This pattern willresult in an image that would be produced by a converging specklepattern originating from the downward displaced plane, propagatingthrough the speckle pattern's true birth spot, and diverging startingfrom this spot, despite that in fact the speckle pattern would originatefrom the coherent light illuminated spot (i.e. its birth spot).

It should be noted that focusing on a downward displaced or far fielddownward displaced plane may be very useful when the imaging unit is tooclose to the surface of interest: if imaging unit requires toospecialized details (e.g. lenses) and/or if the imaging surface is notin the far field of the object of interest (far field of the specklepattern original spot). The imaging unit then may be focused at adownward displaced plane being in the far field of the surface ofinterest; stationarity property will appear thanks to the principle ofreversibility of light.

Considering the use of the stationarity, the motion of interest (or themotion of the certain region of the surface of interest) can beextracted from spatio-temporal trajectories of speckles. The extractioncan be based on motion estimation (ME) techniques including those basedon block matching algorithm (BMA), parametric/motion models, opticalflow, and pel-recursive techniques. The extraction is facilitated due tothe speckle pattern stationarity. When the latter is present, it allowsidentifying the surface of interest (or at least a region of the surfaceof interest) in different frames and considering the motion of thissurface of interest (or at least of the region of the surface ofinterest) as motion of a rigid body. Therefore, the stationarity allowstracking a certain region of the surface of interest or the entiresurface of interest, and extracting from its motion a special type ofmotion, for example, oscillatory motion associated with sound. It shouldbe noted, that it occurs quite frequently, that the motion of interestis a superposition of various motions, one or more of which is/are of aspecial type, e.g. of vibration type, pertinent to the application inwhich the surface is used.

The technique of the present invention allows, for example, detection ofsounds produced by a remote source. These sounds may be distorted orweak when they reach an observation point or may not reach such a pointat all. The sounds can be associated with surfaces the motions of whichinclude movements besides the sound vibrations. The technique alsoallows separate detection of several sounds, which is useful when two ormore sounds are produced simultaneously. In fact, different soundsources may be imaged by different regions of a pixel detector array(PDA) of an imaging unit. Thus, the technique is useful for example forextracting speech of several persons speaking at the same time.Accordingly, the typically present in acoustical techniques need for theblind source separation becomes reduced or absent. As well, thetechnique of the present invention is useful for extracting speech ofeven one person in a noisy environment, present for example in anightclub or in nature in case of respective weather conditions.

The technique of the invention is interference-based, but it does notrequire an interferometer: a speckle pattern generated at a surfaceilluminated by a spot of laser beam (the so-called “secondary specklepattern”) is actually a localized self-interfering pattern. In coherentspeckle patterns each individual speckle serves as a reference pointfrom which changes in the phase of light can be tracked.

The technique of the present invention also provides a leeway forpositioning an imaging unit relatively to the moving surfaces (e.g.surfaces of sound sources or surfaces of objects experiencingsound-caused vibrations). The leeway is due to the divergence of thespeckle pattern: speckles are due to diffuse reflection and they areformed spatially small (initially their size is of about the opticalwavelength), therefore their diffraction occurs in a wide angle (closeto 2π steradians). Consequently, independently on a location of theimaging unit, but provided that the imaging unit is correctly oriented,it can collect speckles. However, for the extraction of motion, theimaging unit location in the far field of the surface of interest ispreferred.

The inventors have considered applications of their technique fordetection of various motions, including those associated with sounds,such as speech and heartbeats. For detection of speech the inventorshave imaged speckle patterns formed by reflection of coherent infraredlight from a human body, in particular from human head, cheeks,cheekbones, or throat. For facilitation of the detection of speech, theimaging unit has been operated with a sampling rate of 10 KHz, i.e. witha sampling rate larger than 8 KHz, the average Nyquist frequency ofspeech. The Nyquist frequency of speech may be lower, therefore invarious embodiments of this technique, the imaging unit sampling ratemay be for example between 2 KHz and 4 KHz, or 4 KHz and 8 KHz, orhigher than 8 KHz.

A motion detection system may include an imaging unit, an illuminationunit (e.g. a laser), and an extraction unit (e.g. a computer programmedto extract speech or heart beat vibrations from spatio-temporaltrajectories of the speckle-pattern, or an application-specificintegrated circuit, ASIC, configured to extract vibrations). The imagingunit may include PDA and optics adapted for imaging the relevant specklepattern. The PDA and optics may have one or more of its characteristics,such as resolution, pixel size, aperture size and focal length,determined by or limited by an expected object distance (i.e. anexpected distance from the imaging unit to the surface of interest).

For example, when a surface associated with speech is located relativelyfar away, the speckle pattern reaching an in-focus forward displaced orfar field forward displaced plane may be large: the scale of the specklepattern generated at the surface of interest increases proportionally toa distance from the surface of interest. An objective (e.g. one or morelens) of the imaging unit projects the speckle pattern onto the PDA andtypically demagnifies the scale of the speckle pattern. The imaging unitis to be configured so at to collect a sufficient number of speckleswithin the imaged speckle pattern and so as to resolve the speckles inthe collected pattern. Therefore, the aperture of the objective of theimaging unit is to be selected sufficiently large for collecting atleast several speckles from a speckle pattern propagating from theremote surface of interest. The focal length of the objective is to beselected sufficiently large and the pixel size of the PDA is to beselected sufficiently small for resolving the speckles of the collectedspeckle pattern. Possible selections of the optics and PDA parametersdepend on the motion detection system application.

The selection of the imaging unit parameters can depend also onadditional factors such as a size of the coherently illuminated spot onthe surface of interest, desired PDA frame rate and sensitivity, anavailable PDA size or pixel count. For example, the size of thecoherently illuminated spot is related to the PDA frame rate and PDApixel size and count. In fact, if between two frames the surface ofinterest moves too much, there might be no region of this surface thatwould be illuminated and imaged in both frames: the illuminating lightmight fall onto a completely new region of this surface during theimaging of the second frame or even not fall on this surface at all, orspeckles reflected from the intersection of the two illuminated regionsmight miss the imaging unit during the imaging of the second frame. Thelatter case can for example occur if the reflection from the illuminatedintersection of two regions moves outside the PDA. Therefore, the sizeof the coherently illuminated spot, dependent on a cross-section of theilluminating beam, can be made smaller, if the PDA frame rate is madelarger. In general, a product of these two parameters is larger if anexpected speed of the motion of interest is larger. Similarly, ingeneral, the PDA pixel count has to be larger if expected amplitude orexpected region of the motion of interest is larger. It should be noted,however, that in some embodiments the illuminating beam and/or imagingunit can be operated to follow the certain region of the surface ofinterest and/or the speckles generated at this region.

In accordance with the above, the parameters of the motion detectionsystem can be optimized for various applications. For example, if a PDAof a relatively high frame rate is needed in the imaging unit, theoperational wavelength of the motion detection system can be maderelatively short, i.e. the wavelength can be from the visible spectrumrather than from the infrared. This relates to the fact that, typically,PDAs for infrared light are slower than PDAs for visible light. Also,optics is typically larger for infrared light.

The choice of the motion detection system operational wavelength can bebased also on a desired covertness of the illuminating beam and on adesired safety of use of the illuminating beam. For example, wavelengthof illuminating light can be chosen to be outside the visible spectrum.

Considering types of motion that can be detected by the technique of theinvention, the following should be noted. Generally, a motion of asurface can be split into such components as transversal motion, axialmotion, and tilt (the axis connects the surface of interest with theimaging unit). The technique of the invention has an enhancedsensitivity to the tilt, which on the imager sensing plane (PDA)primarily causes speckle pattern shifting. The transversal motion of thesurface of interest causes shifts and changes of the speckle patternimage, but in cases when imaging utilizes focusing on a displaced (e.g.forward or downward displaced) plane thus caused shifts are oftensignificantly smaller than the shifts caused by the tilt. Moreover, ifthe displaced (e.g. forward displaced) plane is in the far field of thespeckle pattern source spot, these shifts become suppressed: the effectof the transversal motion becomes restricted mostly to a change of thespeckle pattern phase. The third motion component, the axial motion,causes scaling of the speckle pattern. However, in many applicationsaxial coordinate of the surface of interest changes only slightlyrelatively to an axial distance between the imaging unit and the surfaceof interest; axial motion thus may or may not significantly affect thespeckle pattern image. As a result, the technique of the invention isprimarily useful for extraction of the tilting motions, thoughdetermination of a trajectory of the surface of interest is notprecluded, even when the motion of interest has all three namedcomponents.

In this connection, it should be understood that in some applicationsextraction of all motion components is not required. For example, theinventors experimented with human speech extraction. In most cases, theobtained speech was recognizable despite that the extraction had beenperformed using an assumption that the speckle pattern had moved only asa result of the tilt (the assumption was not in fact required).

The inventors have also experimented with vibrations of body parts. Inthese experiments, they contactlessly detected heart beats of experimentparticipants. The obtained heart beats were repeatable for the sameparticipant and differed from participant to participant. The inventorsthen developed a concept of optical cardiogram (OCG). OCG can be usedfor determining health conditions, for authentification, in liedetectors.

There is thus provided, according to one broad aspect of the invention,a method of imaging an object. The method includes imaging a coherentspeckle pattern, propagating from the object, by an imaging system beingfocused on a plane displaced from the object.

The displaced plane may be located between the imaging system and theobject; or further from the imaging system than the object.

For example, the displaced plane may be located further than D²/4λ fromthe object, D and λ being respectively a size and a wavelength of thespeckle pattern at the object. This plane is thereby in a far field ofthe object.

In some embodiments of the invention, illumination of the object withcoherent light is used to form the coherent speckle pattern.

The imaging method may be used for imaging the object while moving. Themovement may be associated with a vibration, e.g. of a living body'spart.

The vibration may correspond to a speech, a sequence of heart beats, aheart beat resolved to a heart beat's structure, as well as vibration ofa cloth on a living body.

The living body's part may be at least one of a hand joint, a chest, athroat, a temporal fossa, a stomach, a throat, a cheekbone, a head.

In some other embodiments of the invention, the vibration of a vehicle's(e.g. car's) part is detected. The vehicle's part may be an interiorpart, e.g. a part of vehicle's engine; or an exterior part.

Preferably, the imaging is repeated at least two times for obtaining asequence of at least two speckle pattern images.

For example, the method may include extracting the speech from asequence of images of a living body part, extracting the sequence ofheart beats, extracting the heart beat's structure. The method mayinclude comparing the extracted heart beat's structure with a heartbeat's structure of the same heart; comparing the extracted heart beat'sstructure with a heart beat's structure of a different heart.

The method may be used in motion detection. To this end, a shift betweenregions of an object which appear in first and second images of theobject is determined. Each of these regions includes a stationaryspeckle pattern formed by light originated at the same region of theobject and imaged by focusing on a plane which is displaced from theobject and located in a far field of the object.

Preferably, the shift determination is repeated at least two times so asto obtain a sequence of shifts. In some embodiments of the invention,the obtained sequence of shifts is compared with another sequence ofshifts.

According to another broad aspect of the invention, there is provided amethod for use in motion detection. The method includes determining ashift between regions of an object which appear in first and secondimage of the object, each of the regions including a stationary specklepattern formed by light originated at the same region of the object andimage by focusing on a plane which is displaced from the object and islocated in a far field of the object.

According to yet another broad aspect of the invention, there isprovided a system for use in motion detection. The system includes asource of a beam of coherent light and an imaging system, the imagingsystem being capable of being focused on a plane displaced from anintersection of the beam and a field of view of the imaging system andbeing in a far field from the intersection.

The focusing (in-focus) plane may be located between the imaging systemand the intersection location; or further from the imaging system thanthe intersection location.

The detection system may include a processing unit associated with saidimaging system. The processing unit is configured and operable todetermine a shift between two images of a speckle pattern originated atthe intersection location.

In its yet further aspect, the invention provides a memory (technicalmemory) including data indicative of a sequence of images of astationary coherent speckle pattern originated at a subject, the databeing indicative of the subject's heart beats and/or heart beatstructure, the sequence being thereby enabled for use in determinationof at least one physiological parameter.

The at least one physiological parameter may include at least one fromthe following: a heart beat rate, heart beat structure, and opticalcardiogram.

The stored data may include the sequence of images of the stationarycoherent speckle pattern originated at the subject; or a sequence ofshift values between the images in the sequence of images of thestationary speckle pattern originated at the subject, the shift valuesbeing indicative of the subject's heart beat rate.

The sequence may include an image of at least one of a hand joint, achest, a throat, a temporal fossa.

In yet further aspect, there is provided a memory including dataindicative of a sequence of images of a stationary speckle patternoriginated at a subject, said sequence being indicative of the subject'sspeech.

The stored data may include the sequence of images of the stationaryspeckle pattern; or a sequence of shift values between the images of thestationary coherent speckle pattern, the sequence being indicative ofthe speech. The sequence may be taken with a rate between 2 and 4 KHz; arate between 4 KHz and 8 KHz; a rate exceeding 8 KHz. The sequence mayinclude an image of at least one of a throat, a cheekbone, a head.

There is also provided a memory including data indicative of a sequenceof images of a stationary speckle pattern originated at a vehicle, theimages being indicative of vibrations associated with the vehicle andthe sequence being indicative of the vehicle operation.

The stored data may be indicative of an image of a region of thevehicle's interior, e.g. vehicle's engine; and/or an image of a regionof the vehicle's exterior.

The invention also provides a device comprising the above-describedmemory, and one or more processors configured for determining a sequenceof shift values between the images in the sequence of images of thestationary speckle pattern; and/or a spectrogram of a sequence of shiftvalues between the images in the sequence of images of the stationaryspeckle pattern. The device might be configured as or include a computer(e.g. programmed computer).

BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the invention and to see how it may be carriedout in practice, embodiments will now be described, by way ofnon-limiting example only, with reference to the accompanying drawings,in which:

FIG. 1 is a schematic illustration of an imaging system utilizing theprinciples of the present invention;

FIGS. 2A-2D illustrate respectively the following: (A) The image of theloudspeakers; (B) Graph of evolution of speckle pattern positioncaptured from the left loudspeaker; (C) The reconstructed spectrogram ofthe left loudspeaker; (D) The reconstructed spectrogram of the rightloudspeaker.

FIGS. 3A-3G illustrate the following: (A)-(B) Two sequentially capturedspeckle patterns; (C) The defocused image of an experiment participantand of a speckle pattern propagating from the participant's throat; (D)Two examples of evolution of the speckle pattern position; (E) Zoomedone of the two previous examples, along with smoothed graph of evolutionof the speckle pattern position; (F) Vibrations extracted from theprevious example of evolution of the speckle pattern position; (G)Spectrogram of a speech signal (a scream) corresponding to thevibrations of the previous example.

FIGS. 4A and 4B illustrate the following: (a) Vibrations of the specklepattern position caused by heart beat; (b) The spectrogram of the signalof 3A.

FIGS. 5A-5F show various Optical Cardiograms, obtained with thetechnique of the invention, in frequency domain (the graphs middle markscorrespond to the zero frequency).

FIGS. 6A-6F show various Optical Cardiograms, obtained with thetechnique of the invention, in time domain.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Referring to FIG. 1, there is schematically illustrated an imagingprocess of a secondary speckle pattern generated at a surface of amoving diffusive object. Imaging is performed by an imaging unit 10 attwo instances: when the diffusive object is at a position andorientation DO₁ and when the diffusive object is at a position andorientation DO₂. The imaging unit 10 includes an imaging lens L and apixel detector array PDA. The imaging unit is configured for focusing ona forward displaced plane IF. At both instances, the speckle pattern isformed as a reflection of coherent light beam LB (e.g. laser beam). Thespeckle pattern propagates to the in-focus plane, where it takes a formSP_(IF,1) in the first instance and a form SP_(IF,2) in the secondinstance. The speckle pattern continues to propagate: it crosses thein-focus plane and reaches the imaging unit, so that a portion of thespeckle pattern gets collected by the imaging lens. For assessing andusing a variation between speckle patterns imaged at differentinstances, the inventors have used a model according to which the objectsurface shape illuminated by the laser beam spot is not changed in timeinterval between two frames (i.e. is not changed between two subsequentimaging instances). In other words, the object surface shape has beenassumed to be stationary (e.g. rigid).

With regards to speckle patterns the following should be noted. Specklepatterns are self interfered random patterns having relatively randomamplitude and phase distributions. So-called “primary speckle patterns”can be generated by passage of illuminating light through a diffuser ora ground glass. So-called “secondary speckle patterns” can be generatedby reflection of illuminating light from the diffuse surface of anobject.

A movement of a rigid object surface can be presented as a superpositionof basic movements of three types: transverse, axial, and tilt.Typically, all three of these components will be present in thesuperposition. However, these movements are translated differently onthe PDA plane. The inventors have found that, due to the forwarddisplaced positioning of the in-focus plane of the imaging unit, tilttends to produce the major effect on the speckle pattern and this effecttends to be in the speckle pattern shifting.

In fact, considering the effects of the three components one by one, thefollowing is noted. The first, transverse, component of the objectmovement is manifested in the transverse shifting of the forming specklepattern. This shift is demagnified by the imaging unit after projectionof the speckle pattern on the image plane (PDA plane). The transverseshift of the projected on the PDA speckle pattern can be expressedthrough a causing this shift transverse shift ΔX of the object: theshift of the pattern equals ΔX/M, where a demagnification factor Mequals (Z₂+Z₃−F)/F, Z₂ is a distance between the object and the in-focusplane, Z₃ is a distance between the in-focus plane and the lens, and Fbeing a focal length of the lens. The shift can be written also asΔXF/(Z_(t)−F), Z_(t)=Z₂+Z₃ being a total distance from the lens to theobject. If the imager (imaging unit) is focused at a plane being in thefar field of the original speckle pattern spot, the effect of thetransverse component reduces to a change of the phase of the specklepattern.

The second, axial, component of the object's movement, is manifested ina change of a scale of the imaged speckle pattern. This change isrelatively small, as it is demagnified by the imaging unit. In terms ofFIG. 1, while for the object being in position DO₁ demagnificationfactor equals M=(Z₂+Z₃−F)/F, for object in position DO₂ this factor willequal (Z₂+Z₃+ΔZ−F)/F, ΔZ being an axial shift between position DO₁ andDO₂. The relative change of the demagnification factor will equal(Z₂+Z₃+ΔZ−F)/(Z₂+Z₃−F)−1. The relative change can be written also as(Z_(t)+ΔZ−F)/(Z_(t)−F)−1=ΔZ/(Z_(t)−F).

Incidentally, the third, tilt, component of the object motion affectsthe speckle pattern similarly to the first, transverse, component of theobject motion: as a result of the tilt the speckle pattern in the PDAplane shifts. However, in counter distinction with the shift caused bythe transverse component, the shift caused by the tilt becomes moreimportant when the imaging unit is focused on a plane closer to theimaging unit and further from the object, as the latter shift equalsZ₂Δα/M_(IF)=Z₂FΔα/(Z₃−F), Δα being the tilt, M_(IF) being ademagnification factor for plane IF. This shift can be written also as(Z_(t)−Z₃)FΔα/(Z₃−F).

It can be seen from the above, that imaging the speckle pattern withfocusing on a forward displaced plane and with focusing on the objectleads to different results. While in the latter case the relevantcondition Z₃≈Z_(t) results in that a motion of a remote object (i.e. forwhich object distance Z_(t)>>F) may not translate into a significantmotion of the speckle pattern, even if the motion has all threecomponents, in the former case the relevant condition Z₃<Z_(t) resultsin that the speckle pattern on the PDA plane can move a distance usefulfor detection, if the motion has a tilt component. In other words, itcan be concluded that even a slight movement of the object can bemagnified to significant shifts in the PDA plane if the movementcontains tilt component, the object is sufficiently far from the imagingunit, and the in-focus plane is sufficiently close to the imaging unit.Imaging the speckle pattern with focusing on an object leads rather to achange of the speckle pattern than to its shift when the object moves.

It should be noted, that increasing focal length F up to values close toobject distance Z_(t) might magnify the lateral shift in the PDA planeto significant values in the case of the imaging unit being focused onthe object. However, this would typically require increasing anobjective length to overly large values. Indeed, in the case ofobjective consisting of a single lens, the objective length, i.e. thelength between lens L and pixel detector array PDA, equalsZ_(t)F/(Z_(t)−F). If focal length F would be close to object distanceZ_(t), and the object would be relatively remote, the objective lengthmight need to be very large.

In the case of the imaging unit being focused on a forward displacedplane, the task of magnifying lateral shift may be fulfilled somewhatsimilarly, by the selection of the position of the forward displacedimaged plane close to a focal plane (i.e. by selecting Z₃≈F). However,in this case the focal length does not have to be close to objectdistance Z_(t); and therefore while an increase in the objective lengthmay be needed, this increase generally may be smaller.

The case of the imaging unit focused on a downward displaced plane canbe considered similarly to the case of the imaging unit focused on aforward displaced plane.

As it is clear from above, the inventors' technique provides aconvenient for measuring shift of a speckle pattern generated at theobject's surface. The shift can be provided by focusing the imaging uniton a plane being closer to the imaging unit than the object or beingfurther from the imaging unit than the object. Particularly, the imagingunit may be focused on a plane being in the far field of the object. Theinventors also considered selection of other parameters of the detectionsystem.

For example, the invented motion detection technique can employ trackingof the speckle pattern or of a region of the speckle pattern through anumber of images (frames). Tracking may follow intensity maxima of thespeckle pattern. In such a case these intensity maxima need to beresolved by the imaging system.

As it is known, at a distance Z₂ from the speckle-forming spot of a sizeD an average speckle size reaches λZ₂/D. Herein λ is a wavelength oflight.

A resolution of the speckle pattern imaged at the sensor plane (i.e. thePDA plane) equals (in the case of imaging focused at a front removedplane):

$\begin{matrix}{{\delta\; x} = {{\frac{\lambda\; Z_{2}}{D} \cdot \frac{1}{M_{IF}}} = {\frac{\lambda\; F}{D} \cdot \frac{Z_{2}}{Z_{3} - F}}}} & (1)\end{matrix}$

In some embodiments, this resolution is larger (and therefore is notlimited by) than the optical and the geometrical resolution of theimaging unit. In particular, in some embodiments, the PDA has a pixelsize p smaller than one, or a half, of the average speckle δx. If thepixel size p is K times smaller than the average speckle, then a typicalspeckle will be sensed by K pixels in the PDA plane. The lattercondition can be written as:

$\begin{matrix}{F = \frac{{{Kp}( {Z_{3} - F} )}D}{Z_{2\;}\lambda}} & (2)\end{matrix}$

In some embodiments, it can be approximated as

$\begin{matrix}{F \approx \frac{{KpZ}_{3\;}D}{Z_{2}\lambda}} & (3)\end{matrix}$

The latter approximation is useful in particular in those cases in whichthe objective length is selected to be relatively small; for exampleonly slightly larger than the focal length F.

Further, in some embodiments, it can be approximated as

$\begin{matrix}{F \approx \frac{{KpZ}_{3}D}{Z_{t}\lambda}} & (4)\end{matrix}$

Approximation (4) is useful when the imaging system is configured fordetection of relatively small object tilts which need the highestpossible magnification, but without a significant increase in theobjective length.

Imaging the same speckle with more than four pixels may be redundant.Therefore, in some embodiments, the pixel size is larger than a quarterof the averaged speckle size.

For speckle pattern tracking, a number of speckles collected by the PDAin every dimension needs not be too small, otherwise a correspondencebetween speckle patterns from different frames might not be established.The number of collected speckles in a single dimension of the PDAequals:

$\begin{matrix}{N = {{A\;\frac{Z_{2}}{Z_{t}}\frac{1}{M_{IF}\delta\; x}} = {\frac{AD}{\lambda\; Z_{t}} = \frac{FD}{F_{\#}\lambda\; Z_{t}}}}} & (5)\end{matrix}$Here A is a diameter of the aperture of the lens, in the respectivedimension; F_(#) is an F-number of the lens. The latter relation isobtained thanks to large divergence of the speckle pattern, making theaperture of the lens to be filled with the speckles. In someembodiments, the number of speckles N is larger than 2 and smaller than4. In some other embodiments, the number of speckles N is larger than 4and smaller than 8. Yet in some other embodiments, the number ofspeckles N is larger than 8 and smaller than 10. Yet in some otherembodiments, the number of speckles N is larger than 10 and smaller than16. Yet in some other embodiments, the number of speckles N is largerthan 16 and smaller than 20, or larger than 20.

The pixel count of the PDA, in any dimension, may need to be larger thanKN. For example, in some embodiments it is larger 2 times than 20, i.e.larger than 40.

The tracking of the speckle pattern may be facilitated if the specklepattern is stationary or quasi-stationary, i.e. if it mostly shifts inthe PDA plane, without significantly changing its topology and scale.The (quasi-) stationarity can be provided if the in-focus plane is inthe far field of the speckle-forming light spot. For example, somequasi-stationarity may be provided if the distance Z₂ between thespeckle-forming light spot and the in-focus plane is larger than D²/4λ.

The origin of the far field condition can be clarified by comparingimaging of the speckle pattern with focusing close and far from thespeckle-forming spot. The field formed by the speckle pattern needs tobe considered in detail. It may be assumed that the object surface addsto the phase of coherent illuminating field a random phase distributionφ(x,y), (x,y) being coordinates at the surface of the diffusive object.

Considering first a case of the imaging unit utilizing focusing onto aplane close to the speckle-forming spot, for a plane being in the closefield of the object (at a small distance Z₁ from the object) the lightfield distribution is:

$\begin{matrix}{{T_{m}( {x_{o},y_{o}} )} \propto {\int{\int{{\exp\lbrack {{\mathbb{i}}\;{\phi( {x,y} )}} \rbrack}{\exp\lbrack {\frac{\pi\;{\mathbb{i}}}{\lambda\; Z_{1}}( {( {x - x_{0}} )^{2} + ( {y - y_{0}} )^{2}} )} \rbrack}{\mathbb{d}x}{\mathbb{d}y}}}} \propto {{A_{m}( {x_{o},y_{o}} )}{\exp\lbrack {{\mathbb{i}}\;{\psi( {x_{o},y_{o}} )}} \rbrack}}} & (6)\end{matrix}$

The above field T_(m)(x_(o), y_(o)) has spatially non-uniform amplitudeA_(m)(x_(o), y_(o)) and phase Ψ(x_(o), y_(o)), where (x_(o), y_(o)) arecoordinates in the plane close to the object. The field T_(m)(x_(o),y_(o)) is calculated as a Fresnel integral for the random phase φ,introduced by the surface of the diffusively reflective object.

Formula (6) is based on the paraxial approximation (the argument of thesecond exponent in (6) is quadratic). It also relies on the assumptionof a uniform reflectivity distribution in the illuminated region of theobject surface. The above two assumptions are made for convenience; theydo not unnecessarily restrict the presented here imaging technique.

The distribution (6) can be imaged by the imaging unit. The spatialintensity distribution at the image plane is:I(x _(s) ,y _(s))=|∫∫T _(m)(x _(o) ,y _(o))h(x _(o) −Mx _(s) ,y _(o) −My_(s))dx _(o) dy _(o)|²  (7)Here h is a spatial impulse response of the imaging unit, (x_(s), y_(s))coordinates in the sensor (light sensitive) plane, and M is thedemagnification (inverse magnification) of the imaging unit. The spatialimpulse response h takes into account optical and sensor (e.g. PDA)blurring. It is defined on the sensor plane.

If the object surface experiences a tilt, the light field at the closeto object plane changes:

$\begin{matrix}{{{A_{m}( {x_{o},y_{o}} )} \propto {\begin{matrix}{\int{\int{{\exp\lbrack {{\mathbb{i}}\;{\phi( {x,y} )}} \rbrack}{\exp\lbrack {{\mathbb{i}}( {{\beta_{x}x} + {\beta_{y}y}} )} \rbrack}}}} \\{{\exp\lbrack {\frac{\pi\;{\mathbb{i}}}{\lambda\; Z_{1}}( {( {x - x_{o}} )^{2} + ( {y - y_{o}} )^{2}} )} \rbrack}{\mathbb{d}x}{\mathbb{d}y}}\end{matrix}}}{\beta_{x} = \frac{4\pi\;\tan\;\alpha_{x}}{\lambda}}{\beta_{y} = \frac{{4\pi\;\tan\;\alpha_{y}}\;}{\lambda}}} & (8)\end{matrix}$

Here, angles α_(x) and α_(y) are the tilt components relative to the xand y axes; factor of four in β_(x) and β_(y) includes factor of twowhich accounts for the double contribution of tilt into the opticallength traveled by light on its way to the detector. The optical lengthis doubly affected because, for example for a part of the surface ofinterest reproaching the detector, light has, first, to travel more onits way to the surface of interest and, second, has to travel more afterreflection at the surface of interest on its way to the detector. It isseen from (8) that the speckle pattern will change due to the tilt.

The change (caused by the tilt) of speckle pattern at the close toobject plane causes a change in the spatial intensity distribution atthe image plane. The latter change is enhanced, due to the blurring ofsmall speckles with the impulse response of the imaging unit having alarge magnification factor. The magnification M can be as high as fewhundred. Basically, while the lens is focused on the object or on aplane close to the object, the image of the speckle pattern is variedrandomly with tilt of the object (and motion including tilt of theobject). Thus, tracking the object motion by imaging the secondaryspeckle pattern with an imager focused on the object surface or veryclose to it is a problem.

Additionally, the focusing on a plane being very close to the object ofinterest can prevent resolving the imaged speckle pattern. For smalldistances Z₁ the average speckle at the imaged plane is small. This isseen from (1), where distance Z₁ replaces Z₂. If the average specklesize is too small, speckle pattern may not be resolved by the sensor.Therefore, a speckle pattern associated with the aperture of the lensrather than with the object surface may becomes dominant. An averagespeckle of the latter speckle pattern is λF_(#). It coincides with theblurring width of aperture.

However, when the focusing on a plane remote from the object surface isconsidered, secondary speckle pattern generated by the object becomesdominant and stationary. Defocusing, with respect to the object plane,yields a decrease of the magnification factor M (the decrease may be byone or more orders of magnitude). Defocusing also brings the imagedplane into the far field.

Equations (6) and (7) in the far field become:

$\begin{matrix}{{{T_{m}( {x_{o},y_{o}} )} \propto {\int{\int{{\exp\lbrack {{\mathbb{i}}\;{\phi( {x,y} )}} \rbrack}{\exp\lbrack {\frac{{- 2}\pi\;{\mathbb{i}}}{\lambda\; Z_{2}}( {{xx}_{o} + {yy}_{o}} )} \rbrack}{\mathbb{d}x}{\mathbb{d}y}}}} \propto {{A_{m}( {x_{o},y_{o}} )}{\exp\lbrack {{\mathbb{i}}\;{\psi( {x_{o},y_{o}} )}} \rbrack}}}\mspace{20mu}{and}} & (9) \\{\mspace{79mu}{{I( {x_{s},y_{s}} )} = {{\int{\int{{T_{m}( {x_{o},y_{o}} )}{h( {{x_{o} - {M\; x_{s}}},{y_{o} - {My}_{s}}} )}{\mathbb{d}x_{o}}{\mathbb{d}y_{o}}}}}}^{2}}} & (10)\end{matrix}$

In (9) the exponent quadratic in coordinates (x,y) is omitted from theintegral as this exponent affects phase and amplitude at all points (x₀,y₀) equally. According to (9) and (10), speckle pattern barely changesand shifts as a result of transversal movement. In fact, the transversalmovement does not affect the amplitude of the Fourier transform in (9).Also, the magnification of the blur function h in (10) is smaller thanit would be with focusing on the object. Axial movement also almost doesnot affect the speckle pattern. Only a constant phase is added in (9)and the magnification of the speckle pattern is slightly changed.

In the far field, tilting causes shifting of the speckle pattern (as itwas mentioned above). This is confirmed by the following equation (11),analogous to equation (8):

$\begin{matrix}{{{A_{m}( {x_{o},y_{o}} )} = {\begin{matrix}{\int{\int{{\exp\lbrack {{\mathbb{i}\phi}( {x,y} )} \rbrack}{\exp\lbrack {{\mathbb{i}}( {{\beta_{x}x} + {\beta_{y}y}} )} \rbrack}}}} \\{{\exp\lbrack {\frac{{- 2}\pi\;{\mathbb{i}}}{\lambda\; Z_{2}}( {{xx}_{o} + {yy}_{o}} )} \rbrack}{\mathbb{d}x}{\mathbb{d}y}}\end{matrix}}}{\beta_{x} = \frac{4{\pi tan}\;\alpha_{x}}{\lambda}}{\beta_{y} = \frac{4\pi\;\tan\;\alpha_{y}}{\lambda}}} & (11)\end{matrix}$

According to (11) tilt can be compensated by a shift of the origin ofthe coordinate system (x_(o), y_(o)). In other words, tilt introducesinto the integral in (11) a phase linear in coordinates (x,y); thisphase causes the shift in the Fourier plane (x_(o), y_(o)). This shiftis proportional to the tangent of the tilt angle. Equations (8) and (11)tend to describe the light field more accurately for close to normal,with respect to the surface of interest, angles of laser illuminationand speckle pattern detection.

The inventors have experimented with several embodiments of the inventedmotion detection system. In the first series of experiments, theinventors optically detected and extracted sounds produced byloudspeakers. A photograph of the loudspeakers is shown on FIG. 2A. Theloudspeakers were approximately 1 meter away from both a camera (imagingunit) and a coherent light source; they did not move. The camera wasBasler A312f; it could capture up to 400 frames per second in arelatively small window of interest. The laser was a frequency-doubledNd:YAG laser with output power of 30 mW at wavelength of 532 nm. Theilluminating laser light was passed through a ×10 lens (with pinhole)positioned side by side with the camera. The illumination spot was about5 mm in diameter. Both loudspeakers were illuminated by the laser, insequence. The resulting speckle patterns were imaged with the camera,equipped with a TV lens of a focal length of 16 mm and F-number between5.6 to 8. The camera was focused on a downward displaced surface beingapproximately 20 m behind the loudspeakers. The pixel size of the cameraPDA was 8.3×8.3 microns. The camera was controlled with Matlab.

In the experiment, the inventors sent an excitation signal of anascending temporal frequency to the left loudspeaker and an excitationsignal of a descending frequency to the right loudspeaker. The cameracaptured a sequence of 5000 frames in 12.207 seconds. The camera framerate was 409.6 frames per second (fps), it corresponded to the Nyquistfrequency of 205 Hz. In the first frame of the sequence the inventorsselected two regions of 10×10 pixels (samples) from regionscorresponding to plastic covers of the loudspeakers (not fromloudspeakers' membranes). The samples were taken for both the left andthe right loudspeaker. For both samples, their positions in other frameswere extracted. Then, from these position sequences, spectrograms forsounds of the loudspeakers were calculated. The extraction of soundsthus relied on vibrational motions of walls of loudspeakers' covers.Vibrations changed covers' tilts.

An exemplary temporal sequence of sample position, along one axis, ispresented in FIG. 2B. The sample position changed due to motions of thecover of the left loudspeaker. The sample position, in the PDA plane,was extracted by the correlation of sequential frames. The position wasnormalized for convenient plotting. In the inset a portion of the sampleposition temporal sequence is shown zoomed.

The position temporal sequence in FIG. 2B was obtained by a search of ashift of the selected sample between sequential frames. For each pair ofsequential frames, a sweep through various possible shift values wasdone; that shift value was selected to be the shift between the twoframes of the pair, that produced a maximum correlation between theselected sample being in the first frame and a shifted from it by theshift value 10×10 region in the second frame. Due to noises, not in allframes the selected sample could be found: in some cases there was no10×10 region in the second frame that would match the selected samplewith a high correlation peak. Those frames which did not show a highcorrelation peak with their previous or subsequent frames had shiftsthat corresponded to high frequencies and that could be filtered out forthe experiments.

From the position temporal sequences of the left and right loudspeakers'covers, the inventors calculated spectrograms. To this end the Matlabfunction “specgram” was utilized. The function used a default window of256 frames for calculating “instantaneous” spectra (i.e. forapproximating it). In FIG. 2C there is presented a spectrogramreconstructed from the left loudspeaker. The spectrogram is atime-frequency representation of the analyzed signal temporal sequence:in the spectrogram, the horizontal dimension represents time and thevertical dimension represents frequency. Each thin vertical slice of thespectrogram shows the spectrum during a short period of time, usingwhiteness to stand for amplitude. Whiter areas show those frequencieswhere the simple component waves have higher amplitude. It is noted,that the spectrogram reconstructed and shown in FIG. 2C matches theloudspeaker excitation signal of the ascending frequency.

In FIG. 2D there is presented a spectrogram reconstructed from the imagesequence containing the right loudspeaker. For the reconstruction thesame digital processing was used as in the previous example. Here aswell the spectrogram matches the excitation signal sent to theloudspeaker.

In another series of experiments the inventors applied their techniquefor extraction of human voice signals (singing of one of the inventors)played on the loudspeakers. As in the previous series of experiments,they illuminated the loudspeakers with coherent light and imaged themwith a camera focused on a removed plane.

The obtained two sequences of images were processed in several stepsperformed on an appropriately programmed computer. In the first step, asample was selected and a time dependence of its position in the image(PDA) plane was determined (for each of two sequences). In the secondstep, a low pass filtering was applied to the sample position timedependence and the filtered signal was subtracted from the dependence(for each of two sequences); frequencies corresponding to the inventor'svoice were kept in the difference. The signals were purified: only thoseimages (sequence frames), which provided a high likelihood(signal-to-noise ratio, more than 10) of finding the sample in theseimages, were kept. The signals could be enhanced by using interpolationprior to shift finding for each signal and using larger samples. Aswell, they could be enhanced by iterating the process of finding thehigh SNR samples, by increasing sample pixel size in the iterationprocess. Likewise, shifts finding can also be iterated. Even without theadditional enhancement obtained samples vibrations were indicative ofthe singer's voice sounds. This was verified by transforming thereconstructed signals into suitable electrical signals, exciting theloudspeakers with the electrical signals, and listening to the producedsounds.

In another series of experiments the inventors have optically detectedand extracted human speech signals, produced by an experimentparticipant (one of the inventors). The participant not only talked, butalso moved during the experiments (the loudspeakers from the previousexperiments did not move for reasons unconnected with production ofsound). For sound detection, imaging of speckle pattern originating fromone of the participant's throat, face (in particular cheekbone), back ofthe head and other regions of the head was, in various experiments,performed. The imager (camera) was focused on a forward displaced planebeing closer to the camera than the source of the speckle pattern. Inexperiments, the inventors used the same Basler A312f camera with amatrix of 782×582 pixels. Shutter rates were between 40 to 100microseconds, in frequency units between 25 KHz to 10 KHz, the gain(internal parameter of the camera) was 192. The camera was used with aComputar telecentric lens of the focal length 55 mm and F-number 2.8.The camera speed was almost independent of a number of pixels in a usedregion of the matrix. The inventors used samples of sizes 20×20 and20×40 pixels. A Suwtech double Nd-YAG laser at power between 1 and 20 mWand wavelength 532 nm was used for creating speckle patterns.

In FIGS. 3A and 3B there are shown 20×20 samples of two sequentiallytaken speckle patterns. In FIG. 3C there is presented a defocused imageof the inventor. The image is defocused, since the camera was focused ona forward displaced plane. The speckle pattern originates from theinventor's throat.

Speckle pattern images were sequentially correlated for sample shiftfinding. The found differential displacements of the sample wereaccumulated. In FIG. 3D there are presented two examples R₁ and R₂ ofthe sample trajectory on the imaging plane (i.e. PDA). A part of theupper trajectory and its sliding average are shown in a greater detailedview in FIG. 3E. The lines are denoted R₁ and A₁, respectively. Theslidingly averaged real trajectory, i.e. the trajectory A₁, correspondsto the person's principal movement (mostly tilt). Vibrations of realtrajectory R₁ around the filtered trajectory A₁ correspond to theperson's speech.

In FIG. 3F there is shown a difference between the real and smoothedtrajectories of the speckle pattern. Deviation of the trajectory fromits sliding average can fully or partially correspond to person'sacoustical movements (tilting vibrations). Thus, the sliding voicespectrum of the difference between real and smoothed trajectories isindicative of the human speech. The sliding spectrum can be found byslidingly transforming the deviation temporal dependence into thefrequency domain and selecting from this domain the voice frequency band(e.g. the telephony voice frequency band ranging from approximately 300Hz to 3400 Hz). The sliding time interval on which the transformation isdone may be 10 ms. For the detection and extraction of speech, shift ofthe speckle pattern in any direction on the PDA plane can be utilized.

In FIG. 3G there is shown a spectrogram calculated from the timeevolution of the speckle pattern position on the PDA. The vertical axisshows sound frequency in Hz. The horizontal axis shows time, in tenthsseconds (0.1 s). The person screamed during the imaging; the scream isreflected by band S being at relatively high frequencies in thespectrogram (approximately 120 Hz).

The inventors performed simulations for a design of several more speechdetection setups. In the simulations, they used 2 cm as a value of thediameter of illumination spot (i.e. D=2 cm).

For wavelength of 400 nm, focal length F=10 mm (a fairly small value)and f-number of F#=1 (i.e. aperture diameter of φ=10 mm), a maximalobject distance was calculated to be approximately Z₂ ^((max))=500 m.Decreasing aperture diameter φ (increasing the f-number F#) willdecrease Z₂ ^((max)). A suitable camera-in-focus plane distance wascalculated to be between 20 cm and 6 m. The calculation was done so thatthe far field condition was preserved. For wavelength of 2 microns andf-number of F#=1 the inventors obtained maximal object distance Z₂^((max)) of about 100 m. A suitable interval for the in-focus planedistance Z₃ did not change.

For wavelength of 400 nm, focal length F=1000 mm (a fairly large value)and f-number F#=1 (i.e. aperture diameter φ=1000 mm), the calculatedmaximal object distance Z₂ ^((max)) was about 50 km, while thecalculated minimal in-focus plane distance Z₃ ^((max)) was about 3 km.Again, these values were calculated for preservation of the far fieldapproximation. Also, a maximal in-focus plane distance can be estimatedsuch that the far field condition is preserved. For wavelength of 2microns, the inventors obtained for the same conditions (D=2 cm andφ=1000 mm) that the maximal object distance is Z₂ ^((max))=10 km.

In yet another series of experiments the inventors have used theirtechnique to detect the assistant's heart beats. To this end, theyimaged speckle pattern originating from the assistant's chest, coveredwith a cloth. In FIG. 4A there is shown a time dependence of theextracted by correlation sample shift. The time axis is drawn in units,five thousands (5000) of which correspond to 20 seconds. The signal (theshift of the correlation peak) is measured in pixels (or in pixelunits). In FIG. 4B there is shown a spectrogram of the signal. The heartbeats are well distinguishable. Thus, the invented technique allowscontactless monitoring of the human heart rate. This contactlessmonitoring can be utilized in hospitals for monitoring patients, inrescue operations for detecting living signs of victims of theaccidents, and in sports and physical training. The heart beats can alsobe contactlessly detected by imaging of a speckle pattern produced athand joint.

The inventors' technique can be used not only for detection of presenceof heart beats, but also for determination of such medical parameters asheart beats rate (i.e. pulse) and blood pressure and forcharacterization of physical strain, experienced by an individual (ahuman or an animal). This should become useful in medicine, veterinarymedicine, and agriculture. Moreover, the inventors' technique can beused for obtaining optical cardiograms (OCGs). An OCG can be built froma sequence of images of a stationary speckle pattern, wherein theseimages are indicative of vibrations associated with vibrations of heartand the sequence is indicative of heart beats. The latter conditionmeans that the sequence, preferably, has to be taken with a rateexceeding the Nyquist rate for heart beats. OCG can be used not only fordetermining health conditions, but also for authentification, as OCGappears to be an individualized repeatable characteristic.

The inventors have performed a series of experiments in which they usedOCG for determination of pulse and characterization of physical strain.In the experiment, they illuminated experiment participants' body partswith a Nd:YAG laser working at wavelength of 532 nm and imaged reflectedcoherent speckle patterns with a digital camera model Pixel Link A741.The camera and the laser were positioned side by side. The participantswere separated by a distance of about 1 m from the camera. The camerawas focused on a far range of about 20 m. For vibration extraction,spatial regions (samples) of 128 by 128 pixels were utilized. Thecorrelation plane was 256×256 pixels; the correlation peak appearedsomewhere close to its center.

Referring to FIG. 5A there is shown a frequency representation (Fouriertransform) of a time-dependence of a coordinate of the same sample foundin a sequence of speckle pattern images. In other words, there is shownthe Fourier transform of OCG or OCG in frequency domain. Specklepatterns originated from a Subject's hand joints. Images were taken at arate 20 Hz. Five hundred (500) images (frames) were taken and theresulting spectral resolution therefore was 1/(500/20)=0.04 Hz. TheFourier transform was performed over a sequence of 490 frames; theseresolution units were used for frequency axis in the FIG. 5A. Thefrequency is zero at the central, highest, peak of the Fouriertransform, positioned at 245 units in the plot (the Fourier transform isshifted from 0, since it is plotted in the plot units). The plot issymmetric, because the temporal signal is real. The next highestspectral peak is located at mark 279. This peak corresponds to heartbeats occurring with a rate 0.04 (279−245) Hz=1.36 Hz. A controlmeasurement was performed with Polar Clock; its result was 1.33pulses/sec.

The pulse rate measurement was repeated for the same Subject (#1) atphysical strain. The respective Fourier transform is shown in FIG. 5B.This time the highest non-central peak was at a mark 287 and pulse rate0.04 (287−245) Hz=1.68 Hz. The respective Polar clock measurement was1.783 (pulses per second).

Four next measurements were performed at a rate of 100 Hz; 1000 imageswere taken in time windows of 10 seconds. In the first measurement ofthese four, the control Polar Clock measurement gave the result of 1.033pulses per second, for a Subject #2 at rest. Since the spectralresolution was 1/(1000/100)=0.1 Hz and 990 frames participated in thespectral computation, the peak had to appear at mark1.033/0.1+495=505.3. In fact, in FIG. 5C the peak appears at mark 506.In the second measurement, performed for Subject #3 experiencingphysical strain after physical activity, the Polar Clock measurement was1.433 pulses per second; therefore the peak had to appear at mark1.433/0.1+495=509.3. The peak appeared at mark 509 (FIG. 5D). In thenext measurement the Polar Clock result was 1.216 Hz, for a Subject #3at rest; therefore the peak was anticipated at mark 1.216/0.1+495=507.2.The peak was obtained at mark 507 (FIG. 5E, this time the specklepattern originated from Subject's throat). In the last measurement ofthe four, the Polar Clock measurement was 1.5 pulses per second, forSubject #3 at physical strain, and therefore the peak was anticipated atmark 1.5/0.1+495=510. Indeed, inventors received the peak at mark 510(FIG. 5F, the speckle pattern originated from Subject's throat).

Thus, it is seen that the inventor's technique is capable of being usedfor contactless heart rate measurement.

Further, the inventors have performed a series of experiments thatshowed that OCG is highly individualized characteristics. Theexperiments were performed with the same setup used in the examples ofFIGS. 5C-5F. The imaging rate was 100 Hz. In FIG. 6A there is shown anOCG in time domain of a Subject #4, with a single period of this OCGenlarged in the inset. This single period can be sufficient for use assignature, as the OCG generally repeats itself in other periods. In FIG.6B there is shown an OCG of a Subject #5. This OCG also generallyrepeats itself. The signatures of Subjects #4 and #5 look different; andbeats of Subject #5 in general have a high correlation with each otherand a low correlation with beats of Subject #4. Beats of each subjectpreserve their unique temporal shape. In FIGS. 6C and 6D there arepresented OCGs of a subject #6 at rest in different days. The signaturesare alike, despite the time period passed between the measurements. InFIGS. 6E and 6F there are presented OCGs of Subjects #7 and #8.Different Subjects have indeed different signatures.

Hence, OCG appears to carry a unique signature of a person as forexample finger prints or retina prints. OCG therefore can be used as anentrance key to secured areas. On the other hand, OCG also carriesinformation about person's medical and/or strain condition. This forexample can be used in a lie detector: when a person lies, his OCG willchange and this can be detected with the technique of the presentinvention.

Similarly to the above examples, the technique of the inventors can beused for biomedical imaging of a fetus. The vibrations of fetus may beexcited by ultrasound. The reflected from fetus sound waves can beimaged by the technique of the inventors in addition or rather thanacoustically.

Somewhat similarly to the OCG example, the technique of the inventorscan be used for diagnostics and recognition or authentification ofvehicles. An imperfection of car engine work often results in specificto this imperfection sound or disruption of the engine's sound; manydrivers and mechanics use these specifics to find the cause of theimperfection. However, such diagnosing by listening is difficult, partlybecause of the noise done by engine, partly because of the limitedhearing of humans. Also, the source of the sound often may not be easilylocalized. Using the technique of the inventors allows detecting andcharacterizing various engine and vehicle sounds, even while they stillare weak for the human ear; and it also allows localizing the sounds'sources. Also, the optical detection allows achieving a higher precisionover the acoustical detection. Thus, the technique of the inventors willbe useful not only for establishing the source of failures, but also forpreventing them at the early stages. This entails a possibility of abetter maintenance of vehicles.

In view of the above, applications of the technique of the inventors tothe diagnostics of vehicles can use one or more sequence of images of astationary speckle pattern, wherein these images are indicative ofvibrations associated with a vehicle and the sequence is indicative of avehicle operation. These images may be (defocused) images of a vehicle'sengine part or parts. The images may also be (defocused) images of avehicle's wheel system or transmission. The vehicle may be operated withidling engine; the vehicle may have wheels which may be or may not berotated by the engine. The sequence may be stored in a memory, such asmemory of a general purpose computer, or memory of a specialized device,or a memory carrier (e.g. an operative memory, a video memory, a compactdisc, an optical disc, a hard drive disc, a flash memory device, etc).The vehicle itself may be a car, a ship, a locomotive, an air plane, ahelicopter, or any other which operation or which engine operation isassociated with mechanical vibrations. The vehicle diagnostics may alsoutilize a set of image sequences taken at different engine rates and/orfor different vehicle parts.

The technique of the inventors can also be used in home land securityapplications. For example, it can be utilized for distinguishingvehicles, e.g. cars (for these purposes, license plates are currentlyused). In particular, it can be utilized for finding camouflagedvehicles. Similarly appearing vehicles can be distinguished for exampleby their engines, which have different vibrating signatures. In motion,though that the engine is hidden in the vehicle's inside, vibrations aretransferred to the vehicle's outside, and therefore the vibrations canbe found by the defocused imaging of speckle patterns formed onvehicle's exterior (e.g. hood, body, wind shields).

Those skilled in the art will readily appreciate that variousmodifications and changes can be applied to the embodiments of theinvention as hereinbefore described without departing from its scopedefined in and by the appended claims.

The invention claimed is:
 1. A method for use in motion detection of anobject, the method comprising: providing a system comprising a source ofa beam of coherent light and an imaging system capable of being focusedon a plane displaced from an intersection of the beam and a field ofview of the imaging system and being in a far field from saidintersection; operating said system for illuminating an object by thebeam of coherent light, and imaging the coherent speckle pattern,originated at and propagating from the object, while focusing theimaging system on a plane being in a far field of the object and beinglocated further than D²/4λ from the object, D and λ being respectively asize and a wavelength of the speckle pattern at the object.
 2. Themethod of claim 1, wherein said displaced plane is located between theimaging system and the object, or is located further from the imagingsystem than the object.
 3. The method of claim 1, wherein the object ismoving.
 4. The method of claim 3, wherein the movement is associatedwith a vibration of at least one of the following: vibration of a livingbody's part, and a cloth on a living body.
 5. The method of claim 3,wherein the movement is associated with a vibration, said vibrationcorresponding to at least one of the following: a speech, a sequence ofheart beats, a heart beat resolved to a heart beat's structure, and ablood pressure.
 6. The method of claim 5, wherein the imaging isrepeated at least two times for obtaining a sequence of at least twosaid speckle pattern images.
 7. The method of claim 6, comprising:processing image of the object obtained by said imaging of the coherentspeckle pattern propagating from the object, said processing comprisingat least one of the following: extracting the speech from said sequence;extracting the sequence of heart beats, extracting the heart beat'sstructure, extracting the heart beat's structure and comparing it with aheart beat's structure of the same or different heart.
 8. The method ofclaim 3, wherein the movement is associated with a vibration of a livingbody's part, said vibration corresponding to a speech.
 9. The method ofclaim 3, wherein the movement is associated with a vibration of a livingbody's part, said living body's part being at least one of a hand joint,a chest, a throat, a temporal fossa, a throat, a cheekbone, a head, astomach.
 10. The method of claim 3, wherein the movement is associatedwith a vibration, said vibration being that of a vehicle's part.
 11. Themethod of claim 10, wherein said vehicle's part comprises at least oneof vehicle interior or exterior parts.
 12. The method of claim 10,wherein said vehicle's part is a part of vehicle's engine.
 13. Themethod of claim 1, comprising: determining at least one shift betweenregions of the object which appear in at least first and second imagesof the object, each of said regions including the stationary specklepattern formed by light originated at the same region of the object andimaged by focusing the imaging system on the plane which is displacedfrom the object and located in the far field of the object; anddetermining motion of the object along transverse, axial, and tiltdimensions.
 14. The method of claim 1, comprising determining a shiftbetween regions of the object which appear in first and second images ofthe object, each of said regions including the stationary specklepattern formed by light originated at the same region of the object andimaged by focusing the imaging system on the plane which is displacedfrom the object and is located in the far field of the object.
 15. Asystem for use in motion detection, the system comprising: a source of abeam of coherent light and an imaging system, said imaging system beingcapable of being focused on a plane displaced from an intersection ofthe beam and a field of view of the imaging system and being in a farfield from said intersection; and a processing unit associated with saidimaging system, said processing unit being configured and operable todetermine a shift between two images of a speckle pattern originated atthe intersection location, said processing unit being configured forcommunication with a device comprising a memory unit, comprising dataindicative of a sequence of images of a stationary coherent specklepattern originated at a subject, being indicative of the subject's heartbeats and/or heart beat structure, said sequence being thereby enabledfor use in determination of at least one physiological parameter. 16.The system of claim 15, wherein said plane is located either between theimaging system and the intersection location or is located further fromthe imaging system than the intersection location.
 17. A system of claim15, wherein said processing unit is configured for determining at leastone of the following: a sequence of shift values between the images inthe sequence of images of the stationary speckle pattern; and aspectrogram of a sequence of shift values.
 18. The system claim 15,wherein said plane is located further than D²/4λ from the intersectionlocation, D and λ being respectively a size and a wavelength of aspeckle pattern originated at the intersection location, said planethereby being in a far field of the intersection location.
 19. Thesystem of claim 15, wherein the processing unit is configured to operatethe imaging system to repeat imaging at least two times for obtaining asequence of at least two images of the speckle pattern.
 20. The systemof claim 15, wherein the processing unit is configured for processing animage of the intersection location obtained by imaging of the coherentspeckle pattern propagating from the intersection location, saidprocessing comprising at least one of the following: extracting a speechfrom said sequence; extracting the sequence of heart beats, extracting aheart beat's structure, extracting a heart beat's structure andcomparing it with a heart beat's structure of the same or differentheart.
 21. A system for use in for use in motion detection, the systemcomprising: a source of a beam of coherent light and an imaging system,said imaging system being capable of being focused on a plane displacedfrom an intersection of the beam and a field of view of the imagingsystem; and a processing unit associated with said imaging system, saidprocessing unit being configured and operable to determine a shiftbetween two images of a speckle pattern originated at the intersectionlocation, wherein said processing unit is configured for communicationwith a device comprising a memory unit comprising data indicative of asequence of images of a stationary speckle pattern originated at asubject, said sequence being indicative of the subject's speech.
 22. Thesystem of claim 21, wherein said data comprises at least one of thefollowing: the sequence of images of the stationary speckle pattern; anda sequence of shift values between the images of the stationary coherentspeckle pattern, said sequence being indicative of the speech.
 23. Thesystem of claim 21, wherein said sequence comprises an image of at leastone of a throat, a cheekbone, a head.
 24. The system of claim 21,comprising a processor for determining a spectrogram of said sequence ofshift values, said sequence being taken with a rate of 2 kHz or higher.25. The system of claim 21, wherein said plane is located either betweenthe imaging system and the intersection location or is located furtherfrom the imaging system than the intersection location.
 26. The systemof claim 21, wherein said plane is located further than from theintersection location, and being respectively a size and a wavelength ofa speckle pattern originated at the intersection location, said planethereby being in a far field of the intersection location.
 27. Thesystem of claim 21, wherein the processing unit is configured to operatethe imaging system to repeat imaging at least two times for obtaining asequence of at least two images of the speckle pattern.
 28. The systemof claim 21, wherein the processing unit is configured for processing animage of the intersection location obtained by imaging of the coherentspeckle pattern propagating from the intersection location, saidprocessing comprising at least one of the following: extracting a speechfrom said sequence; extracting the sequence of heart beats, extracting aheart beat's structure, extracting a heart beat's structure andcomparing it with a heart beat's structure of the same or differentheart.
 29. A system for use in for use it motion detection, the systemcomprising: a source of a beam of coherent light and an imaging system,said imaging being capable of being focus on a plane displaced from anintersection of the beam and a field of view of the imaging system; anda processing unit associated with said imaging system, said processingunit being configured and operable to determine a shift between twoimages of a speckle pattern originated at the intersection location,wherein said processing unit is configured for communication with adevice comprising a memory comprising data indicative of a sequence ofimages of a stationary speckle pattern originated at a vehicle, theimages being indicative of vibrations associated with the vehicle andthe sequence being indicative of the vehicle operation.
 30. The systemof claim 29, wherein said plane is located either between the imagingsystem and the intersection location or is located further from theimaging system than the intersection location.
 31. The system of claim29, wherein said plane is located further than from the intersectionlocation, and being respectively a size and a wavelength of a specklepattern originated at the intersection location, said plane therebybeing in a far field of the intersection location.
 32. The system ofclaim 29, wherein the processing unit is configured to operate theimaging system to repeat imaging at least two times for obtaining asequence of at least two images of the speckle pattern.
 33. The systemof claim 29, wherein the processing unit is configured for processing animage of the intersection location obtained by imaging of the coherentspeckle pattern propagating from the intersection location, saidprocessing comprising at least one of the following: extracting a speechfrom said sequence; extracting the sequence of heart beats, extracting aheart beat's structure, extracting a heart beat's structure andcomparing it with a heart beat's structure of the same or differentheart.
 34. A method for use in motion detection of an object, the methodcomprising: providing a system comprising a source of a beam of coherentlight and an imaging system capable of being focused on a planedisplaced from an intersection of the beam and a field of view of theimaging system; operating said system for illuminating an object by thebeam of coherent light, and imaging the coherent speckle pattern,originated at and propagating from the object, by an imaging systembeing focused on a plane displaced from the object; and determining atleast one shift between regions of the object which appear in at leastfirst and second images of the object, each of said regions includingthe stationary speckle pattern formed by light originated at the sameregion of the object and imaged by focusing the imaging system on theplane which is displaced from the object.
 35. The method claim 34,wherein said plane is located further than D²/4λ from the object, D andλ being respectively a size and a wavelength of the speckle pattern atthe object.
 36. The method of claim 34, comprising utilizing thedetermined at least one shift between said regions of the object, anddetermining motion of the object along transverse, axial, and tiltdimensions.
 37. The method of claim 36, wherein the object is moving.38. The method of claim 37, wherein the movement is associated with avibration of at least one of the following: vibration of a living body'spart, and a cloth on a living body.
 39. The method of claim 38, whereinthe movement is associated with the vibration corresponding to at leastone of the following: a speech, a sequence of heart beats, a heart beatresolved to a heart beat's structure, and a blood pressure; a vibrationof a living body's part being at least one of a hand joint, a chest, athroat, a temporal fossa, a throat, a cheekbone, a head, a stomach; avibration of a vehicle's part comprises at least one of vehicle interioror exterior parts.
 40. The method of claim 39, wherein the imaging isrepeated at least two times for obtaining a sequence of at least twosaid speckle pattern images.